NTNU-1$@$ScienceIE at SemEval-2017 Task 10: Identifying and Labelling Keyphrases with Conditional Random Fields
Erwin Marsi, Utpal Kumar Sikdar, Cristina Sánchez Marco, Biswanath Barik, Rune Sætre · 2017
We present NTNU's systems for Task A (prediction of keyphrases) and Task B (labelling as Material, Process or Task) at SemEval 2017 Task 10: Extracting Keyphrases and Relations from Scientific Publications (Augenstein et al., 2017).Our approach relies on supervised machine learning using Conditional Random Fields.Our system yields a micro F-score of 0.34 for Tasks A and B combined on the test data.For Task C (relation extraction), we relied on an independently developed system described in (Barik and Marsi, 2017).For the full Scenario 1 (including relations), our approach reaches a micro F-score of 0.33 (5th place).Here we describe our systems, report results and discuss errors.